EFFICIENT STORAGE AND COMPRESSION OF COVERING ARRAYS USING ADVANCED ENCODING TECHNIQUES

Abstract

This paper introduced a novel storage format for covering arrays, designed to optimize file size through efficient compression techniques. The proposed format employed Asymmetric Numeral System (ANS) encoding for array data, as well as Run-Length Encoding (RLE) and Variable Length Encoding (VLE) for metadata storage. The goal was to provide a compact, standardized format that facilitates easier sharing and utilization of covering arrays across different applications. Experimental evaluations on a dataset of 21964 covering arrays from the National Institute of Standards and Technology (NIST) demonstrated that the new format outperforms general-purpose compression algorithms such as ZIP, BZIP2, and XZ in most cases, particularly for larger covering arrays with high parameter counts. While previous work on covering array storage focused on archival and retrieval efficiency, the proposed method significantly reduces storage requirements without loss of structural integrity. The proposed method preserved the combinatorial properties of covering arrays while reducing redundancy, making it a practical alternative for large-scale combinatorial testing applications.